Upload data_utils.py

data_utils.py

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+# Copyright (c) 2022 Graphcore Ltd. All rights reserved.
+
+from typing import Dict, Any
+
+def form_text(example: Dict[str, Any]) -> Dict[str, Any]:
+    """
+    Given an example from the glue mnli dataset, generate a prompt version example in the format: 
+        mnli hypothesis: {hypothesis} premise: {premise} target: {class_label}<|endoftext|>
+    This format can be used to finetune the model as a Causal Languange Model.
+    """
+    hypothesis = example['hypothesis']
+    premise = example['premise']
+    class_label = ['entailment', 'neutral', 'contradiction'][example['label']]
+
+    example[
+        'text'] = f'mnli hypothesis: {hypothesis} premise: {premise} target: {class_label}<|endoftext|>'
+    return example
+
+def split_text(example: Dict[str, Any]) -> Dict[str, Any]:
+    """
+    Given an example in the format
+        mnli hypothesis: {hypothesis} premise: {premise} target: {class_label}<|endoftext|>
+    split it in the prompt to be used for validation (excluding the target) and the class label.
+    """
+    partition = example['text'].rpartition(' ')
+    example['prompt_text'] = partition[0]
+    example['class_label'] = partition[2].replace('<|endoftext|>', '')
+    return example